{"id":"W7023516606","doi":"","title":"Optimization of DNA chip hybridization using mixing with chaotic advection","year":2008,"lang":"fr","type":"other","venue":"OpenGrey (Institut de l'Information Scientifique et Technique)","topic":"DNA and Biological Computing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Chaotic; Mixing (physics); Control volume; Agrégation","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001182758,0.0004429854,0.0004158935,0.0004204496,0.0003551058,0.0001847808,0.0004077703,0.0006773543,0.0002606114],"category_scores_gemma":[0.0003558385,0.0003985744,0.0001506638,0.0006810519,0.0003829818,0.0001762062,0.0002107674,0.0003082618,0.00001866497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002027389,"about_ca_system_score_gemma":0.0006688595,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000954184,"about_ca_topic_score_gemma":0.00005634512,"domain_scores_codex":[0.9976265,0.000268646,0.0008070282,0.0004933762,0.0003702627,0.000434118],"domain_scores_gemma":[0.9976968,0.00002306684,0.001066845,0.0004703517,0.0006078752,0.0001351106],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002666068,0.0003105317,0.001403359,0.001869933,0.0002036126,0.0000170482,0.0008204412,0.5930111,0.3442029,0.00304422,0.002407958,0.05244223],"study_design_scores_gemma":[0.001073463,0.0004842157,0.0003751901,0.003202261,0.0001285553,0.0004044262,0.0001083009,0.1178933,0.6253055,0.00004257834,0.2497245,0.00125768],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02583366,0.0001524523,0.900824,0.0000865653,0.0004600696,0.003770304,0.00005064128,0.00008560311,0.0687367],"genre_scores_gemma":[0.6208371,0.001271158,0.3585055,0.0007030522,0.0004613477,0.000354149,0.003245571,0.0001743804,0.01444782],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5950034,"threshold_uncertainty_score":0.9998466,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01719696021576404,"score_gpt":0.2494173965467706,"score_spread":0.2322204363310066,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}